Nanostructured layers boast countless potential properties — but how can the most suitable one be identified without any long-term experiments?
The goal was to design and deploy a decision-support tool using AI capabilities — mostly predictive analytics — to flag future clinical coronavirus severity.
Optical engineers and biochemists have developed a bio-optics device that enables biologists to create 3D views of clots on a microscopic scale as the clots form.
Eppendorf is introducing VisioNize software, a digital platform designed to deliver valuable services on VisioNize onboard devices. The cloud-based software is designed to facilitate smart laboratory management by minimising instrument downtime as faster corrective actions can be executed in the event of emergencies, hence minimising disruption to laboratory productivity.
Sydney start-ups DetectED-X and LENS Immersive have each launched tools designed to take the pressure off clinicians and hospitals that have been inundated with COVID-19.
InterSystems, a creative data technology provider, has responded to requests from five Australian clinical laboratories gearing up to deal with COVID-19.
Machine learning software called TEXLab forecasts the survival rates and response to various treatments for each individual patient.
Bitplane Imaris 9.5 is a software solution for correlative microscopy, enabling the possibility of opening multiple 2D, 3D or 4D datasets of differing spatial and temporal resolutions in the same scene.
Laboratory scientists and IT experts in industrial, chemical and pharmaceutical fields are expected to benefit from improved productivity and reduced system administration costs with enterprise chromatography data system (CDS) software that can leverage cloud technology to standardise systems for increased connectivity, flexibility and security.
Merck's LANEXO System is a digital laboratory informatics solution designed to reduce time in labs and improve data quality and traceability.
Researchers have managed to make intact human organs transparent, and subsequently used microscopic imaging to reveal the underlying complex structures of these organs at the cellular level.
AI has identified features relevant to cancer prognosis that were not previously noted by pathologists, leading to a higher accuracy of prostate cancer recurrence.